SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3301–3325 of 10420 papers

TitleStatusHype
Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classification—0
Deep Learning Algorithms for Early Diagnosis of Acute Lymphoblastic Leukemia—0
A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification—0
Open Vocabulary Multi-Label Video Classification—0
CAMP: Continuous and Adaptive Learning Model in PathologyCode0
Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays OffCode0
Seq-to-Final: A Benchmark for Tuning from Sequential Distributions to a Final Time PointCode0
SlideGCD: Slide-based Graph Collaborative Training with Knowledge Distillation for Whole Slide Image ClassificationCode0
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic SystemsCode0
GPC: Generative and General Pathology Image Classifier—0
Local Clustering for Lung Cancer Image Classification via Sparse Solution TechniqueCode0
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification—0
Enrich the content of the image Using Context-Aware Copy Paste—0
The Misclassification Likelihood Matrix: Some Classes Are More Likely To Be Misclassified Than Others—0
HDKD: Hybrid Data-Efficient Knowledge Distillation Network for Medical Image ClassificationCode0
Towards a text-based quantitative and explainable histopathology image analysisCode0
FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image ClassificationCode0
Exploring the Boundaries of On-Device Inference: When Tiny Falls Short, Go Hierarchical—0
NoisyAG-News: A Benchmark for Addressing Instance-Dependent Noise in Text Classification—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
CTRL-F: Pairing Convolution with Transformer for Image Classification via Multi-Level Feature Cross-Attention and Representation Learning FusionCode0
Learning to Adapt Category Consistent Meta-Feature of CLIP for Few-Shot Classification—0
An accurate detection is not all you need to combat label noise in web-noisy datasetsCode0
Evaluating the Fairness of Neural Collapse in Medical Image Classification—0
Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketches—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified